The renovation or restoration of color images recorded on silver supports is usually done by processing a digitized version of these altered silver images. The restoration of altered images enables, by visual examination, the image to recover its original colors. The conventional silver supports of the images generally comprise photographic film or paper. In the following description, a silver image means a color image obtained from silver halide photographic emulsions. The alteration or degradation of color images recorded on these silver supports is due for example to aging, or to the exposure of these silver supports to light sources, at the time of handling. Restoration processes of image colors, known to those skilled in the art, consist for example in digitizing an image previously recorded on a silver support (photographic film or paper), and then processing the digitized image in order to restore its colors. These restoration processes consist in transforming the degraded colors on the digitized image, by using the algorithms of image processing software.
The digital image, transformed by the processing, thus has restored colors that approximately match those of the original image.
U.S. Pat. No. 5,796,874 describes the restoration of images printed on a material support, for example paper type, discolored or faded over time. This patent describes a method and means that enable an operator without a high level of skill, to easily restore an image whose colors have been altered. The operator in particular does not have to select and add filters in the scanner used to digitize the image to be restored. But, the operator has to apply image degradation models over time to the image to be restored. That is the restoration is done according to the selection of a time variable: for example, it is assumed that the image is some ten years old and the restoration model for this time (some ten years) is applied in order to restore the colors of the altered image. The restoration method enables a restoration model of the image colors to be obtained and selected automatically, according to a time variable assigned to the image. The image restored in this way can be displayed on a monitor type screen. In addition, the operator can also select another model, linked to another time variable, if the first restoration result was not satisfactory. The correction rule used is applied uniformly to the entire image.
The document of the University of La Rochelle, France, by M. Chambah and B. Besserer, entitled “Digital Color Restoration of Faded Motion Pictures”, and presented to the first International CGIP Conference (Color in Graphics and Image Processing) in Saint-Etienne, France, October 1-4, 2000, describes a method of color restoration of faded images on old films. Firstly, the film is digitized with a scanner; then the coverage effect of the spectral densities of the various dyes is subtracted, by using an adjustment matrix. Secondly, the color channels of the image are balanced using another correction matrix. Finally, the contrast is increased to improve the visual quality. In this method, the correction rule used is applied uniformly to the entire image.
In an article (IEEE Transactions On Image Processing, Volume 9, No. 5, May 2000), entitled “Adaptive Image Contrast Enhancement Using Generalizations of Histogram Equalization”, J. Alex Stark describes a method of contrast enhancement in an image. This method uses a cumulative function of gray levels in a zone or a window (for example with square shape) around a pixel, without interdependence constraint between these zones. The corrections are independent for each image representation zone.
The restoration means of the prior art do not take into account the spatial variations of the alteration of colors in an image. The means of the prior art use mathematical models or functions that take into account certain important parameters that influence the degradation of the colors of an image recorded on photographic film or paper, to then restore the colors of the entire image uniformly.